Intertemporal Risk Management Decisions of Farmers under Preference, Market, and Policy Dynamics

significantly larger than hedging in the value of the full portfolio. This indicates that to the
farmer, an income transfer in terms of subsidy is more valuable than risk reduction of a non-
subsidized instrument like hedging.

Next we take off the transaction cost so hedging has no cost to the farmer. We see from
Table 5 lower panel that optimal hedge ratios generally increase significantly. The rate of the
increase slows down when hedge ratios get close to 79%. The values of the portfolios also
increase slightly when the farmer saves money on hedging. The optimal insurance coverage ratio
still stays at 85% with both 0% and 30% premium loadings, implying that the gain from saving
on hedging still cannot replace the possible loss from lower insurance coverage.

The CE values of each risk management tool change slightly except for hedging (Table
6). The value of hedging goes up by about 35%. Despite that, the ranking of the values for these
tools stays the same, that is, government programs (DP + LDP + CCP) > CI > hedging.

VII. Summary and Conclusions

In this study we apply the GEU maximization framework to analyze a risk management
problem related to wheat production in the PNW. A representative soft white wheat grower in
Whitman County and Grant County, Washington, maximizes his or her utility by selecting an
optimal portfolio of risk management tools including hedging in the futures market, purchasing
crop insurance, and participating in government commodity programs. The GEU model allows
the decision maker to completely specify risk preference, time preference, and intertemporal
substitution preference. It also incorporates other common expected utility maximization models
like CES-EU and MR-EU models as special cases. A very popular but different type of static EU
(MA-EU) model is also added for comparison purpose.

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